AI and NLP Methods for Privacy Policy Analysis: Rule-Based Systems to Large Language Models

This book examines how privacy policies have become objects of computational analysis and what that development means for privacy governance.It traces the field over roughly two decades, following the progression from early rule-based and lexicon-driven systems to machine learning, deep learning, and large language models. This book also reviews the major tasks that have defined automated privacy policy analysis, including classification of data practices, information extraction, corpus and taxonomy development, coverage analysis, compliance-oriented review, and user-facing explanation, while situating privacy policies within a broader accountability ecosystem of contracts, consent flows, governance records, and technical traces. Bringing together research in natural language processing, machine learning, privacy law, and governance practice, this book assesses both what these methods have made possible and where they remain limited.It shows how technical progress has enabled large-sca